The Use of Machine Learning for the Detection and Analysis of Brain Cancer in Imaging

Authors

  • Shaik Masood Ahamed Research Scholar, Department of CSE, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu 600119. India
  • J. Jabez Professor, Department of CSE, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu 600119, India

Keywords:

Tumor Detection, Cancer Analysis, Image Classification, Feature Extraction

Abstract

Brain tumors can develop when cell division proceeds rapidly and unchecked. There is a risk of death if it is not diagnosed and treated in time. Accurate segmentation and classification remains difficult despite multiple important efforts and promising improvements in this sector. Brain tumors are notoriously difficult to diagnose because of their highly variable sizes, shapes, and locations. The goal of this research was to provide academics with a thorough literature on MRI for the diagnosis of brain malignancies. The basics of brain tumors, where to find public datasets, how to enhance them, how to segment them, how to extract features to categorize them, and how to apply deep learning, quantum machine learning and transfer learning to analyze them were all discussed in this overview.

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Published

24.03.2024

How to Cite

Ahamed, S. M. ., & Jabez, J. . (2024). The Use of Machine Learning for the Detection and Analysis of Brain Cancer in Imaging. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 557–566. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5185

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Section

Research Article